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22.03. - 25.03.2021

HEIBRiDS Spring School 2021

Permafrost in the Arctic, which is warming more than four times as fast as the global average, is thawing at an accelerating rate...

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Machine-learning for mapping permafrost landscape dynamics

The Arctic is warming at an unprecedented pace, which leads to rapid landscape changes, particularly in the terrestrial Arctic which is largely underlain by ...

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On the creation of Virtual Research Environments for Data Analytics

The talk will give an overview on digitalization initiatives for earth system sciences within the research field Earth and Environment of the Helmholtz association. ...

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Scalable Processing of Scientific Data in the Age of Data Science

My talk addresses different aspects of of Data Science to emphasize that Data Science comprises of more than machine learning. ...

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Unlocking the Potential of FAIR Data Using AI at Roche Pharma R&D

Artificial intelligence (AI) is playing an increasingly important role in many areas, including the healthcare industry. For life science companies, ...

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Bayesian inference - an introduction and examples of its application to bioinformatics research

The main idea in Bayesian inference is to use probabilities as a way of quantifying the researcher’s degree of belief in different possible states of the world. ...

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Modeling Time Series and Dynamical Systems

I'll discuss (time permitting) three aspects of modeling time series and dynamical systems: ...

29.10. - 30.10.2020

HEIBRiDS Retreat 2020

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Beyond Just Fitting Numbers: Interpretable Artificial Intelligence for the Small Data of Materials Science

The number of possible materials is practically infinite, while only few hundred thousands of (inorganic) materials are known to exist and ...

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Methods for investigating recurrence phenomena in the Earth system

Recurrence is a ubiquitous and fundamental feature in many real world processes. Here, I will focus on recurrence in the system Earth, where it is ...

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Example-driven Data Cleaning

Data cleaning is one of the most time-consuming and tedious tasks in data-driven tasks. Typically, it entails the identification of erroneous values and ...

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Detecting heritable phenotypic traits in images

At the HPI Digital Health & Machine Learning research group, we are developing methods for the statistical analysis of large biomedical data. In particular ...

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From text to categories and beyond: You don't need "deep learning" to do it

In this lecture, we are going to present a group of natural language processing (NLP) methods for multi-class classification of texts which ...

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Learning dynamical laws from data for complex processes

A key task in the field of modeling and analyzing complex processes is the recovery of unknown governing dynamical laws from measurement data only. ...

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Seismology for Earth Imaging in the age of large distributed datasets

Since the first recording of a far-distant earthquake in 1889 seismologists have perceived earthquakes not only as a destructive threat, but as an opportunity ...

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The Virtual Brain

The Virtual Brain is an open-source neuro-informatics platform for brain simulation. In my presentation, I will demonstrate how we use ...

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Big data in space research: requirements and challenges

Big data plays an increasingly important role in space research. Handling of big data on board of satellites poses challenges, which are not yet overcome. As an example, ...

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Data Science in the Manufacturing Domain

The manufacturing domain is known for its high automation level that is achieved by means of a number of cooperating systems in all areas covering ...

ORION: Open Science and your research

This interactive workshop will be an introduction to Open Science is and why it is needed. There will be an overview of the main areas of Open Science: Open Access, Open Data, Public Engagement, practical tips, and engaging activities.

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Covariance-based sparse estimation with applications to channel sounding and massive random access for IoT applications

Consider the following problem: we observe multiple noisy samples from a random vector which can be represented as the linear combination of a small ...

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